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Prediction of ADME/Tox properties, 2D,3D QSAR and molecular docking approach of 2,3-disubstituted-Quinazolin-4(3H)-ones using X-ray crystal structure of Staphylococcus aureus (1T2W) Sortase A

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This study revealed that the major contributing descriptors of 2D QSAR studies are DeltaEpsilonB and DeltaPsiA and 3D QSAR model proves the steric as well as electrostatic effects determine the binding affinity for the drug development. The results of the current computational studies are useful for further designing novel chemical entities of anti-microbial agent.

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Nội dung Text: Prediction of ADME/Tox properties, 2D,3D QSAR and molecular docking approach of 2,3-disubstituted-Quinazolin-4(3H)-ones using X-ray crystal structure of Staphylococcus aureus (1T2W) Sortase A

  1. Cite this paper: Vietnam J. Chem., 2023, 61(4), 495-513 Research article DOI: 10.1002/vjch.202200219 Prediction of ADME/Tox properties, 2D,3D QSAR and molecular docking approach of 2,3-disubstituted-Quinazolin-4(3H)-ones using X-ray crystal structure of Staphylococcus aureus (1T2W) Sortase A Rakesh Devidas Amrutkar1*, Mahendra Sing Ranawat2 1 Department of Pharmaceutical Chemistry, K. K. Wagh College of Pharmacy (Nasik) 422003, Maharashtra, India. Affiliated to Dr Babasaheb Ambedkar Technological University, Lonere-402104 Ph.D. Scholar Rajasthan University of Health Sciences Jaipur, Rajasthan, India 2 B.N. College of Pharmacy, Udaipur-313001, Rajasthan, India Submitted November 30, 2022; Revised February 5, 2023; Accepted March 31, 2023 Abstract New chemical entities of quinazolinone derivatives were used to design as antibacterial agents through selective inhibitors of X-ray crystal structure of Staphylococcus aureus (1T2W) sortase A by the molecular docking using V-Life Sciences MDS version 4.6, software. It is successfully reproduced the binding approach of the crystal structure of the Staphylococcus aureus antagonists. The docking results suggested that the modification in the series that gives better binding potential, hydrophobic Van der Waals, H-bond and charge interactions are responsible for forming the stable compounds of the ligands with receptor. It has been observed that the ligands numbers 4k, 4l, and 4m possess a minimum docking score i.e. minimum binding energy in kilocalorie per mole i.e. these molecules have more affinity for active site of receptor. 2D and 3D QSAR analyses were carried out on quinazoline-4-one derivatives for their antimicrobial activities on S. aureus. The activity of the molecules was transformed into log 1/C. The statistically significant of 2DQSAR and 3D QSAR models are r2 = 0.8066 and q2 = 0.6789 and internal (q2 = 0.7157) and external (predictive r2 = 0.4634), respectively. This study revealed that the major contributing descriptors of 2D QSAR studies are DeltaEpsilonB and DeltaPsiA and 3D QSAR model proves the steric as well as electrostatic effects determine the binding affinity for the drug development. The results of the current computational studies are useful for further designing novel chemical entities of anti-microbial agent. Keywords. 4-(3H)-quinazolinone, molecular docking, 2D and 3D QSAR, X-ray crystal structure of Staphylococcus aureus (1T2W) Sortase A (i.e. receptor site), ADMET. 1. INTRODUCTION chemical entities with enhanced biological activity. A computational modeling tool known as the Structure- and ligand-based methods have proven to quantitative structure-activity relationship (QSAR) be important approaches in early drug discovery and helps to shed light on the relations between the drug design in computer aided drug design. Methods structural characteristics of chemical compounds and of structure-based approaches, which include their biological functions.[4-6] In the field of molecular docking that is regarded among the most medicinal chemistry, chemical agents are very significant method in discovering novel small important for designing novel chemical entities. One chemical entities are based on assessment of the of the scaffold known as a lead compound of connections between the ligand and the active site of antimicrobial drug is quinazoline.[7,8] Quinazoline is the receptor.[1,2] CADD can not only help understand a fused bicyclic heterocyclic skeleton which is relationships between the physicochemical known as benzo-1,3-diazanaphthalene. properties and biological activity of any class of Quinazolinone moiety is found in a variety of molecules, but also provide researchers with deep bioactive natural as well as synthetic products. lots insights about the lead molecules to be used in of natural products contain quinazolinone core further studies to discover new drugs,[3] investigate structures e.g. asperlicin C, sclerotigenin, the pharmacological action of inhibitors, and narrow circumdatin F, benzomalvin A, and many others down the library of derivatives for design of new have been recognized as biologically important 495 Wiley Online Library © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH
  2. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Rakesh Devidas Amrutkar et al. molecules.[9-11] Some synthetic quinazolinones, such bacteria. Sortase A has been attracted great interest as ispinesib, raltitrexed, halofuginone, tempostatin, as potential drug targets since decades.[31] The etc. have been in the market or are currently in inhibition of Sortase A activity results in the clinical trials for various cancer treatments. Various separation of S. aureus from the host cells and chemical entities of quinazolines reported to have ultimately alleviation of the infection. We used these pharmacological effects includes antitubercular,[12,13] newly synthesized active inhibitors to explore the antibacterial,[14] antimicrobial,[15] anti- binding cavity of Staphylococcus aureus Sortase A [16] inflammatory, Antitumor[17] and CNS using V-life docking program. Drug resistance is the depressant[16]antifungal,[18,19] antimalarial,[20] common problem associated with antimicrobial [21] [22,23] antihypertensive, diuretic, inhibition of agents. Chemotherapy will benefit greatly from the derived growth factor receptor phosphorylation,[24] discovery of novel antibacterial agents that may antagonism of ghrelin receptor,[25] anticonvulsant,[26] overcome clinically significant multidrug resistance COX-2 inhibitory activities, analgesic and anti- and have improved pharmacokinetic qualities. It is inflammatory.[27,28] It has been claimed that very likely that a new bacterial inhibitor targeting substituting different functional groups, atoms, or the X-ray crystal structure of Staphylococcus aureus heterocyclic rings at the C-2 or C-3 location of the (1T2W) sortase A binding site will be developed in quinazolinone nucleus can increase the biological the near future is the field’s rapid advancements.[32] activity. For the creation of new bioactive Biological activity and structure of the selected medicines, this quinazoline nucleus with substitution series. Table 1[33-35] is utilized to establish a can be a productive lead molecule.[29] For many quantifiable relationship between the compounds years, molecular docking has been a point of physiochemical properties and biological activities interest. In the current situation, the flexible docking through the performance of molecular docking tool makes protein ligand complex structure studies and QSAR research against X-ray crystal prediction simple. This will provide reasonable structure of Staphylococcus aureus (1T2W) sortase accuracy and speed as well. The binding affinity of Ausing software package QSARpro and MDS 4.6. 4-(3H)-quinazolinone derivatives against the X-ray crystal structure of Staphylococcus aureus (1T2W) O sortase A[30] was analyzed in present investigation. R/Ar N Mainly, enzyme Sortase A involves in the pathogenesis of variety of bacterial infections, X N R2 including respiratory tract, bloodstream, skin and 4a-4t tissue infection which serve to anchor some proteins responsible for virulence mainly by Gram +ve 2,3-disubstitutedquinazolin-4(3H)-ones Table 1: The series of synthesized and evaluated compounds Compound Compound X R2 R/Ar IC50 logIC50 No. Code 1 4a H CH3 H 100 2 2 4b H CH3 NH2 125 2.0969 3 4c H C2H5 H 100 2 4 4d H C2H5 150 2.176 5 4e H C2H5 150 2.176 CH3 6 4f H C2H5 150 2.176 NO2 7 4g H C6H5 H 75 1.875 8 4h H C2H5 25 1.3979 COOH 9 4i H C2H5 100 2 O2N 10 4j H C2H5 -NH2 -- 0 © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 496
  3. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Prediction of ADME/Tox properties, 2D,3D QSA… Compound Compound X R2 R/Ar IC50 logIC50 No. Code 11 4k H C3H7 12.5 1.0969 CH3 12 4l H C3H7 12.5 1.0969 NO2 13 4m H C3H7 12.5 1.0969 COOH 14 4n H C3H7 -- 0 O2N 15 4o H C3H7 -NH2 -- 0 16 4p Br C3H7 100 2 CH3 17 4q Br C3H7 75 1.875 NO2 18 4r Br C3H7 100 2 COOH 19 4s Br C3H7 25 1.3079 O2N 20 4t Br C3H7 -NH2 100 2 2. MATERIALS AND METHODS algorithm approximated a systematic search of positions, orientations, and conformations of the Software packages QSARpro and MDS 4.6 from ligand in the enzyme binding pocket via a series of VLife sciences Pvt. Ltd. in Pune were used for the hierarchical filters. The minimum dock score of current study. QSARpro software was used to example may not be exactly reproducible because conduct simple QSAR research, while MDS this is (GRIP) based run. However, changing the software was used to conduct 3D QSAR studies different input parameters in the GRIP parameters using the kNN-MFA approach (version 4.6). dialog box (like No of Generations, Translation, Rotation limits etc.) can result in dock scoring 2.1. Molecular Docking energies within the desired range and improvement in the orientation of the docked ligand as close to Molecular Design Suite (VLife MDS software that of Co crystallized ligand as possible.[36] package, version 4.6; from VLife Sciences, Pune, India) was used for performing all Docking studies 2.2. 2D, 3D QSAR Studies and conformational analysis. The 2D structure was drawn by Vlife2Ddraw and converted to 3D. Then Calculation of Descriptors this 3D structure is optimized and conformers were generated (Monte Carlo method) and least energy The number of descriptors was calculated after conformers were selected. For preparation of ligand optimization or minimization of the energy of the perform the geometry minimization of the ligand. data set molecules viz. physicochemical, alignment For preparation of protein first download PDB independent and atom type count. Various types of structures (www.rcsb.org) the complex was obtained physicochemical descriptors were calculated: by Merck molecular force field. For preparation of Individual (Molecular weight, H-Acceptor count, H- ligand perform the geometry minimization of the Donor count, XlogP, slogP, SMR, polarisablity, ligand. Merck Molecular Force Fields (MMFF) with etc.), retention index (Chi), atomic valence default settings were used for the ligand connectivity index (ChiV), Path count, Chi chain, minimization. Further docking study was performed ChiV chain, Chain PathCount, Cluster, Pathcluster, by using Grip method. Docking study was Kappa, Element count (H, N, C, S count etc.), and performed in VlifeMDS version 4.6 on Lenovo Polar surface area. More than 200 alignment computer, i3 processors with XP operating system. independent descriptors were also calculated using The GRIP-based ligand docking with genetic the following attributes. © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 497
  4. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Rakesh Devidas Amrutkar et al. 1. Structural descriptors: Topological, equation. This equation explains variation of one or 2. Range: min- 0 and max-7, more dependent variables (usually activity) in terms 3. Selected attributes: 2, T (any), C, N, O, S, of independent variables (descriptors). The QSAR Cl. model can then be used to predict activities for new All the atom type count descriptors were also molecules, for screening a large set of molecules calculated. whose activities are not known. Data Selection Obtaining 3D QSAR models by kNN-MFA method using VLifeMDS For the development of QSAR models all the calculated descriptors were considered as VLifeMDS includes a module that facilitates independent variable and biological activity as evaluation of three-imensional molecular fields dependent variable. In order to evaluate the QSAR around molecules and generates relationship of these model, data set was divided into training and test set fields’ values with the activity. This section using random data selection and manual data illustrates use of the k-nearest neighbor (kNN) selection method. Training set is used to develop the method for generating relationship between activity QSAR model for which biological activity data are and molecular field and provides interpretation of known. Test set is used to challenge the QSAR results thus providing clues for designing new model developed based on the training set to assess molecules. the predictive power of the model which is not included in model generation. 3D QSAR studies Random data selection method: The data was selected randomly entering the percentage of K-Nearest neighbour molecular field analysis (kNN- training set molecules to be selected. The percentage MFA) value was adjusted subsequently in order to get the different sets of training and test molecule. This is The kNN methodology (Ajmani S. et al. 2006) relies based on trial and error method to get the desired on a simple distance learning approach whereby an test set molecules. unknown member is classified according to the Manual data selection method: Data set is divided majority of its kNN in training set. The nearness is manually into training and test sets on the basis of the measured by an appropriate distance metric. The 3D result obtained in random data selection method. QSAR studies were performed by kNN-MFA using stepwise forward backward variable selection Multiple linear Regressions method. In this method the cross-correlation limit set to 0.5 and term selection criterion as q2. F-test ‘in’ All molecules were subjected to regression analysis was set to 4.0, and F test ‘out’ to 3.99. As some using multiple linear regressions, coupled with additional parameters, variance cutoff was set at 0 stepwise forward backward variable selection kcal/mol and scaling to auto scaling; additionally, method. Cross Correlation Limit was set as 0.5, kNN parameter setting was done within the range of Number of Variable in Final Equation was set as 5, 2-5 and prediction method was selected as the Term Selection Criteria as r2, F test In as 4 and F distance-based weighted average. test Out as 3.99. In the ‘Additional Parameter The model was derived by clicking OK, after all Settings’ dialog box Variance Cut-Off was set as 0, the parameters have been set. Once the significant number of random iterations to 10 and the Scaling model is obtained, its fitness plot and contour plot is options was chosen as Auto scaling. After deriving saved. the suitable model, its summary is copied with data fitness plot and contribution chart. Development and validation of QSAR models Obtaining conventional 2D QSAR models using Models were generated by using significant statistical VLifeMDS methods, namely, multiple linear regression (MLR) and kNN-MFA method. The following statistical QSAR Plus module enables evaluation of several parameters were considered to compare the generated molecular descriptors and provides a facility to build QSAR models: correlation coefficient (r), squared the QSAR equation for predicting activity of new correlation coefficient (r2) i.e. q2, predicted r2 molecules. Regression methods are used to build a (pred_r2), and Fischer’s value (F). QSAR model in the form of a mathematical The best way to evaluate quality of regression © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 498
  5. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Prediction of ADME/Tox properties, 2D,3D QSA… model is internal validation of QSAR model. Mostly training and test set in the ratio of 70:30. The leave-one-out (LOO) cross validation method is biological activity was converted to logarithmic used. In this method one object (one biological scale (pIC50) in mathematical operation mode of activity value) is eliminated from training set and software to reduce skewness of data set and then training dataset is divided into subsets (number of used for subsequent QSAR analysis as dependent subsets = number of data points) of equal size. variables. Grid setting for the 3D QSAR shown in Model is build using these subsets and dependent table 2. variable value of the data point that was not included in the subset is determined, which is a predicted Table 2: Grid settings for 2,3-disubstituted value. Mean of predicted values will be same as r2 quniazolin-4(3H)-one and LOO q2 (cross-validated correlation coefficient value) since all the data point will be sequentially From To Interval considered as predicted in LOO subset. Same X -1.83302 19.3129 2.000 procedure is repeated after elimination of another Y -1.04816 16.1648 2.000 object until all objects have been eliminated once. Z -6.74166 7.04288 2.000 (Kubyani, 1994). The leave-one- out (LOO) method indicated the value of q2 (cross-validated explained 2.3. ADME Prediction variance), which is a measure of the internal predictive ability of the model and pred_r2 which is All designed compounds were filtered by predicting a measure of the external predictive ability of the their absorption, distribution, metabolism and model. excretion (ADME) properties by means of Statistical significance of these models was QikpropTool of Schrodinger_2015 (Maestro 10.2 further supported by ‘fitness plot’ obtained for each version). In addition to predicting molecular model; this is a plot of actual versus predicted properties, Qikprop provides ideal ranges of these activity of training and test set compounds and properties for comparing a particular property with provides an idea about how fit the model was trained those of 95% of known drugs. Number properties of and how well it predicts activity of external test set. designed analogues are predicted by Qikprop tool Nearness of experimental to predicted activity is also but here we have reported significant descriptors a tool to determine the statistical validity of models. which are required for predicting drug like Another feature for validation of QSAR model is properties of the molecule. These properties are: value of F test. If the F value is greater than the 1. Rule of five: It includes Molecular Weight tabulated value the equation is statistically (mol_MW) (150-650 Da), Predicted octanol/water significant and has high acceptance criteria.[36] partition coefficient (QPlogPo/w < 5), estimated number of hydrogen bond donor (donorHB ≤ 5), Activity prediction of newer derivatives estimated number of hydrogen bond acceptor (accptHB ≤ 10). Compounds that satisfy these rules After successful development of 2D and 3D QSAR are considered drug-like. models of all the reported series, an attempt was 2. Brain/blood partition coefficient (CNS) (-2 to made to predict the activity of some newer 2). derivatives which has not yet reported and 3. Percent Human Oral absorption (> 80% is synthesized. high, < 25% is poor). This was performed using the Molecular Design 4. Number of possible metabolites (should range Suite (VLife MDS software package, version 4.2; from 1-8) from VLife Sciences, Pune, India), on a Lenovo Obtained results were listed in table 9. computer with Intel Core i3-processor and a window All designed compounds were filtered by XP operating system. predicting their Absorption, Distribution, Metabolism and Excretion (ADME) properties by QSAR studies on 2,3-disubstituted quniazolin- means of swissADME online software in which 4(3H)-one derivative various pharmacokinetic parameters like aq. Solubility, Human GI Absorption, permeability A series of 20 molecules 2,3-disubstituted glycoprotein (Pgp) blood-brain-barrier (BBB) quniazolin-4(3H)-one derivative against penetration, cytochrome P450 inhibition were Staphylococcus aureus were selected to develop estimated for 20 ligands. Obtained results were models for establishing 2D and 3D QSAR models. listed in table 10. The data set of 20 molecules was divided into © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 499
  6. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Rakesh Devidas Amrutkar et al. Toxicity profiling of all the 20 ligands were interactions, and charge interactions are some of the performed by employing by Protox-II -prediction of elements that were taken into account while toxicity of chemicals. Toxicity profile includes predicting the potency or affinity of the ligand to the screening for Hepatotoxicity, carcinogenicity, receptor. The higher the affinity of molecule towards immunotoxicity, mutagenecity Aryl-hydrocarbn the receptor, the more negative the value of the receptor toxicity effects of the ligands were studied energy of binding. The increased Van der Waals by using an online tool. Obtained results were listed interaction indicates that the ligand structure in Table 11 [37] contains more bulky groups due to which Van der Waals interactions were formed. If the charge 3. RESULTS AND DISCUSSION interactions are present, it assists in determining more appropriate binding and thus exhibits more 3.1. Docking Studies affinity to the receptor, adding more efficacies. An automated docking tool used was able to accurately The MDS version 4.6 of V-life software was used to mimic the binding method of the antagonists to examine the intermolecular interactions between the Staphylococcus aureus. 2,3-disubstituted-quinazolin-4(3H)-ones (ligand) and Obtained results were evaluated in terms of the protein X-ray crystal structure of Staphylococcus docking score into the active site of (1T2W) the aureus (1T2W) sortase A, (receptor) obtain from software provides facility of the batch docking of the PDB website. Docking studies were conducted in optimized ligand molecules with the simulated order to advance the anti-microbial behavior of receptor. All ligands are selectively docked A, B, C developed ligands on a structural basis. Scoring chain because each chain of the receptor shows an functions, their binding affinities, and the orientation active site i.e. cavity for docking. We compared the of designed compounds with Staphylococcus aureus dock score of each selected series molecules and antagonistic property were also evaluated. The reference molecule which shows the variation in the receptor’s X-ray crystalline structure served as the docking score, so we predicted that molecules show basis for building the protein-ligand complex. good binding affinity towards the chain B. Utilizing Merck Molecular Force Field (MMFF), the Molecules which show minimum dock score shows planned compounds created with Vlife2-Draw was more affinity for Staphylococcus aureus inhibition transformed into a 3D structure, reducing their and Dock score shown in table 3. According to table energy consumption. The Monte Carlo 3, The ligands 11(4k), 12(4l), and 13(4m) were conformational search ring flip approach was used to initiate to have the lowest dock scores, or the lowest produce conformers. In this comparative docking binding energy in Kcal/mol, indicating that these experiment of designed compounds with known molecules have a higher affinity against active site Staphylococcus aureus antagonist ciprofloxacin with of the receptor. It is understandable that molecules dock score calculated for Chain A-46.619123, for with a lower dock score and binding energy confirm Chain B -21.463950, for Chain C -26.683034 more affinity towards the receptor. kcal/mole. Van der Waals interactions, H-bond Table 3: Docking score of the designed 2,3-disubstitutedquniazolin-4(3H)-one using the X-ray crystal structure of Staphylococcus aureus (1T2W) sortase A Compound Dock Score (kcal/mol) Sr. No. Code Chain A Chain B Chain C 1 4a -27.078984 -25.216152 -26.45678 2 4b -30.332503 -21.326397 -34.623347 3 4c -29.074564 -42.170574 -41.717074 4 4d -29.960979 -34.017140 -32.543211 5 4e -31.153121 -44.182765 -39.567811 6 4f -32.208601 -44.154268 -42.339876 7 4g -30.072532 -36.350709 -32.970050 8 4h -31.326451 -44.438750 -42.567438 9 4i -26.589613 -30.708389 -30.765349 10 4j -35.438010 -32.746665 -33.876544 © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 500
  7. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Prediction of ADME/Tox properties, 2D,3D QSA… Compound Dock Score (kcal/mol) Sr. No. Code Chain A Chain B Chain C 11 4k -31.312991 -48.072841 -48. 336251 12 4l -32.443122 -45.613969 -45.386721 13 4m -33.384442 -44.979478 -44. 613969 14 4n -30.980708 -31.652994 -31. 072841 15 4o -36.455596 -29.177659 -28.776542 16 4p -33.555043 -31.493013 -34.189645 17 4q -29.368680 -37.161157 -37.454461 18 4r -35.972447 -34.345181 -36.765342 19 4s -38.141159 -43.557779 -41.076245 20 4t -27.717890 -25.967020 -28. 493013 Reference Molecule Ciprofloxacin -46.619123 -21.463950 -26.683034 Figure 1: (1T2W) Receptor tube form Figure 2: The active site (Cavity) of 1T2W Figure 3: Active site (Cavity) of 1T2W Figure 4: Active site (Cavity) of 1T2W receptor (Chain A) receptor (Chain B) Figure 5: Active site (Cavity) of 1T2W receptor (Chain C) © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 501
  8. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Rakesh Devidas Amrutkar et al. Interactions of ligands with receptor Reference molecule Ciprofloxacin. This is a reference molecule. It is antimicrobial agent. The low dock score of this molecule is for Chain A-46.61 kcal/mole, for Chain B it is -21.46 kcal/mol and is -26.68 kcal/mol for Chain C. Figure 6: Reference molecule shows the hydrogen and hydrophobic bonding with Chain A of protein Figure 7: 2D-view of the reference molecule show the hydrogen bonding with Chain A Figure 8: Reference molecule show the hydrophobic bonding with Chain B of protein © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 502
  9. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Prediction of ADME/Tox properties, 2D,3D QSA… Figure 9: Reference molecule show the hydrogen bonding with Chain C of protein Molecule (4k). The low dock score of this ligand is -48.072841 kcal/mol against binding site of Chain B of receptor. Figure 10: The (4k) molecule shows the hydrophobic bonding Molecule (4l) Molecule (4m) The low dock score of this ligand is -45.613969 The low dock score of this ligand is -44.9794781 kcal/mole on the binding site of Chain A of receptor. kcal/mole on the binding site of Chain A of receptor. Figure 11: The Molecule (4l) shows the Figure 12: The molecule (4m) shows the hydrophobic bonding hydrophobic binding © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 503
  10. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Rakesh Devidas Amrutkar et al. 3.2. QSAR studies on 2,3-disubstitutedquinazolin- biological activities of the compounds against 4(3H)-one derivative Staphylococcus aureus, a series of 2,3- disubstitutedquinazolin-4(3H)-one analogues were In order to establish a quantitative relationship produced. Table 4 displays the biological activity between the physiochemical properties and and structure of the selected series. Table 4: Biological activity of series of compounds against the Staphylococcus aureus Compound Compound IC50 Compound Compound IC50 logIC50 logIC50 No. Code (MIC g/mL) No. Code (MIC g/mL) 1 4a 100 2 11 4k 12.5 1.0969 2 4b 125 2.0969 12 4l 12.5 1.0969 3 4c 100 2 13 4m 12.5 1.0969 4 4d 150 2.176 14 4n -- 0 5 4e 150 2.176 15 4o -- 0 6 4f 150 2.176 16 4p 100 2 7 4g 75 1.875 17 4q 75 1.875 8 4h 25 1.3979 18 4r 100 2 9 4i 100 2 19 4s 25 1.3079 10 4j -- 0 20 4t 100 2 3.2.1. 2D QSAR of 2,3-disubstitutedquinazolin- chosen as the best model. Table 5 displays 2D 4(3H)-ones derivatives for antimicrobial activity QSAR models that are statistically significant. The values of r2 (squared correlation coefficient), q2 Multiple linear regression analysis (MLR) and the (cross-validated correlation coefficient), pred r2 stepwise forward backward variable selection (predicted coefficient of correlation for the external method were both used in the 2D QSAR analysis to test set), and F (Fisher ratio) value are used to select create 2D models. The manual data selection, the most effective model. The statistical significance random selection, and sphere exclusion methods of the model was revealed by high F-test results. The were used to choose the training and test sets. The r2se, q2se and pred_r2se are the standard errors terms model with the best q2 and pred r2 values was for r2, q2 and pred_r2, respectively. Table 5: Statistical evaluation of 2D-QSAR models 2,3-disubstitutedquinazolin-4(3H)-one derivatives Trials n DOF r2 q2 r2se q2se Pred_r2 Pred_r2se F test 1(Model-1) 14 9 0.8066 0.6789 0.3972 0.5118 0.6491 0.4937 9.3802 2(Model-2) 14 9 0.7953 0.6426 0.5442 0.6011 0.5371 0.4267 8.7390 3(Model-3) 14 9 0.8178 0.7014 0.3651 0.4674 0.3961 0.7289 10.100 The statistically important 2D-QSAR model is and external predictive abilities of 67.89% and shown as follows. 64.91%, respectively, and explains 80.66% (r2 = 0.8066) of the training set's total variance. The F test Interpretation of the model-1 indicates that the model has a statistical probability Model - (Test set: 13, 14, 19, 20, 6 and 9) of 99.99%, which is a failure rate of 1 in 10,000. pIC50 (column) = 38.6253 (DeltaEpsilonB) - Additionally, the randomization analysis 19.7861(DeltaPsiA)-0.3389 (T_C_N_4) + 0.2626 demonstrates confidence in the created model’s non- (T_T_N_2) +0.0020 (I) randomness of 99.9999% (Alpha Rand Pred R2 = Statistics: [n = 14; Degree of freedom = 09; r2 = 0.00000) and was chosen as the QSAR model as a 0.8066; q2 = 0.6789; F test = 9.3822; r2se = result. The F-test score, which is 9.3822, is higher 0.3972;q2se = 0.5118; pred_r2 = 0.6491; pred_r2se = than the calculated value of 3.37. Positive coefficient 0.4937] value of DeltaEpsilonB, a metric for the contribution of unsaturation to biological activity (K Roy, 2011), According to equation (I), model 1 has internal suggested that higher values in QSAR model 1. © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 504
  11. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Prediction of ADME/Tox properties, 2D,3D QSA… 1. Positive DeltaEpsilonB coefficient values on bonds.) According to biological activity, lower biological activity suggested that larger values values result in strong inhibitory activity, lead to good inhibitory activity while lower whereas higher values result in diminished values lead to reduced inhibitory activity (K inhibitory activity. Roy, 2011). 4. T_T_N_2 has a positive coefficient value. (This 2. DeltaPsiA, a molecule's affinity for hydrogen is the number of nitrogen atoms in a molecule bonds, has a negative coefficient value (K Roy, that are single, double, or triple-bonded to one 2011). According to the data on inhibitory another and are spaced apart from any other activity, a lower value is associated with bond by two bonds). Higher values on the improved inhibitory activity, whilst a higher inhibitory activity imply better inhibitory value is associated with decreased inhibitory activity, whereas lower values indicate activity. decreased inhibitory activity. 3. T_C_N_4 negative coefficient value. (This is the number of Carbon atoms in a molecule that are Contribution chart, Data fitness plot and activity single, double, or triple-bonded to any nitrogen of training and test set for model 1 is represented in atom and are separated from one another by four figures 13, 14, 15 and 16, respectively. Figure 13: Contribution plot Figure 14: Fitness plot Figure 15: Training set Figure 16: Test set 3.2.2. 3D QSAR of 2,3-disubstitutedquinazolin- surrounding a set of ligands and constructs 3D- 4(3H)-ones derivatives for antimicrobial activity QSAR models by correlating these 3D fields with the corresponding biological activities. To visualize kNN-MFA samples the steric and electrostatic fields the structural variety in the given set of molecules, © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 505
  12. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Rakesh Devidas Amrutkar et al. molecular alignment was performed. By taking into structure, 2,3-disubstituted quinazolin-4(3H)-one account the common elements of the series as derivative, was employed for alignment. illustrated in figures 17 and 18, the template Figure 17: Template molecules Figure 18: Stereo view of aligned molecules Interpretation The model 1 explains values of k (2), q2 (0.7157), Model-1 (Test set: 4, 5, 6, 7, 8 and 9) pred_r2 (0.4634), q2_se (0.4337), and pred_r2 se (0.5602) prove that QSAR equation so obtained is pIC50 = S_187 8.7713-9.2357 and E_536 2.6295- statistically significant and shows the predictive 3.9609 power of the model is 71.57% (internal validation). Statistics: [kNN = 2; n = 14; DOF = 11; q2 = Statistically significant 3D QSAR models are shown 0.7157; q2_se = 0.4337; pred_r2 = 0.4634; pred_r2se in table 6. Table 7 represents the predicted inhibitory = 0.5602] activity by the model-1 for training and test set. Table 6: Statistical evaluation of 3D-QSAR models of 2, 3- disubstituted quinazolin-4(3H)-one derivatives Trials kNN n DOF q2 q2_se pred_r2 pred_r2se 1 (Model-1) 2 14 11 0.7157 0.4337 0.4634 0.5602 2 (Model-2) 2 14 11 0.6259 0.4836 0.4394 0.6499 3 (Model-3) 2 14 11 0.6473 0.4815 0.2530 0.6494 Table 7: Actual vs. predicted (2D, 3D) antimicrobial activity of 2,3-disubstituted quinazolin-4(3H)-one Compound Compound Sr. No. logIC50 2D-Pred 3D-Pred code no. 1 4a 1 2 2.240364 2.031467 2 4b 2 2.0969 1.524607 2.065433 3 4c 3 2 2.006212 2.000001 4 4d 4 2.176 1.778888 2.031467 5 4e 5 2.176 2.125655 2.041248 6 4f 6 2.176 1.869394 2.038779 7 4g 7 1.875 1.94108 1.0969 8 4h 8 1.3979 1.738621 1.698601 9 4i 9 2 1.2632 1.0969 10 4j 10 0 0.792859 0 11 4k 11 1.0969 0.986065 1.0969 © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 506
  13. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Prediction of ADME/Tox properties, 2D,3D QSA… Compound Compound Sr. No. logIC50 2D-Pred 3D-Pred code no. 12 4l 12 1.0969 0.925849 1.0969 13 4m 13 1.0969 0.765334 1.0969 14 4n 14 0 0.247969 0 15 4o 15 0 0.156436 0.25662 16 4p 16 2 2.114552 2 17 4q 17 1.875 1.967037 1.731095 18 4r 18 2 1.805212 2 19 4s 19 1.3079 1.289157 1.451805 20 4t 20 2 1.359827 1.97716 The data for Plot of contribution chart, fitness activity provides an idea about how well the model plot, training set and test set for model 1 are shown was trained and how well it predicts the activity of in figures 19-22. The plot of observed vs. predicted the external test set. Figure 19: Plot of contribution chart Figure 20: Data fitness plot Figure 21: Training set Figure 22: Test set © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 507
  14. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Rakesh Devidas Amrutkar et al. Steric field, S_187 8.7713-9.2357 positive steric After successful development of 2D and 3D potential is present around the field and hence we QSAR models of all the reported series, the new can use bulky substitution for increase in the chemical entities were drawn and an attempt was activity. made to predict the activity of which has not yet Electrostatic field, E_536 2.6295-3.9609 reported and synthesized. Positive Electrostatic potential is favorable for This was performed using the Molecular Design increase in the activity and hence more bulky Suite (VLife MDS software package, version 4.2; substituent group is preferred in that region. from VLife Sciences, Pune, India), on a Lenovo Design and activity prediction of newer computer with Intel Core i3-processor and a window derivatives shown in table 8. XP operating system. Table 8: Newly designed 2,3-disubstituted quinazolin-4(3H)-one molecules with predicted activities Sr. No. Newly Designed Molecules Predicted activity log O H N 1 6.50862 O2N N O N 2 3.76542 N O N 3 6.43985 Br N O N 4 6.14506 No2 N 3.3. Pharmacokinetic and Toxicity Study were tabulated in tables 9 and 10. Pharmacodynamics properties (toxicity profile) We have analyzed various pharmacokinetic and were also studied number of toxicity profile of pharmacodynamics properties of newly designed designed analogues are predicted by Protox-II tool analogs, Pharmacokinetic properties were aq. but here we have reported significant properties like Solubility, Human GI Absorption, permeability Hepatotoxicity, carcinogenicity, immunotoxicity, glycoprotein (Pgp) blood-brain-barrier (BBB) mutagenecity Aryl-hydrocarbn receptor. From these penetration, cytochrome P450 inhibition by means toxicity studies it was found that ligand 4a, 4d, 4h, of swissADME online software and QikpropTool of 4m, 4p and 4r do not show any type of toxicity. Schrodinger_2015 (Maestro 10.2 version) as a result Compounds 4e and 4k show mutagenicity, all compounds shows high GI absorption, most of Compound 4g shows hepatotoxicity. The results the compounds crosses BBB and Pgp, all were tabulated in table 11. compounds inhibits CYP1A2 except 4h the results © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 508
  15. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Prediction of ADME/Tox properties, 2D,3D QSA… Table 9: ADMET predictions of 2,3-disubstituted quinazolin-4(3H)-one 4a-4t by Qikprop tool #Metabol Qplogpo/ Mol_Mw Molecule Donorhb Absorpti Accpthb Percent Human Oral CNS ites on W 4 a.cdx 160.175 1 3.5 1.124 89.176 0 1 4 a.cdx 160.175 1 3.5 1.03 88.833 0 2 4 b.cdx 175.19 2 4 0.777 83.606 0 1 4 c.cdx 222.246 1 3.5 2.68 100 0 0 4 c.cdx 222.246 1 3.5 2.435 100 0 1 4 c.cdx 222.246 1 3.5 2.676 100 0 0 4 d.cdx 174.202 1 3.5 1.579 92.273 0 1 4 d.cdx 174.202 1 3.5 1.467 93.188 0 2 4 e.cdx 250.299 0 4 3 100 1 1 4 F.cdx 264.326 0 4 3.304 100 1 2 4 g.cdx 295.297 0 5 2.252 87.063 -1 2 4 h.cdx 294.309 1 6 2.495 76.532 -1 1 4 i.cdx 295.297 0 5 2.398 93.918 0 2 4 j.cdx 189.216 2 4 1.163 87.544 0 1 4 k.cdx 278.353 0 4 3.652 100 1 2 4 l.cdx 309.324 0 5 2.578 88.991 -1 2 4 m.cdx 308.336 1 6 2.773 78.171 -2 1 4 n.cdx 309.324 0 5 2.756 100 0 2 4 o.cdx 203.243 2 4 1.516 89.684 0 1 4 p.cdx 357.249 0 4 4.241 100 1 2 4 q.cdx 388.22 0 5 3.163 92.415 -1 2 4 r.cdx 387.232 1 6 3.334 81.459 -1 1 4 s.cdx 388.22 0 5 3.355 100 0 2 4 t.cdx 282.139 2 4 2.064 92.914 0 1 Table 10: ADME predictions of 2,3-disubstituted quinazolin-4(3H)-one 4a-4t by swissADME Compound absorption CYP2C19 permeant XLOGP3 substrate WLOGP MLOGP inhibitor inhibitor inhibitor CYP1A2 CYP2C9 iLOGP Code BBB Pgp GI 4a 1.51 1.17 1.23 1.44 High Yes No Yes No No 4b 1.6 0.13 0.43 1.67 High No No Yes No No 4c 1.8 1.64 1.49 1.75 High Yes No Yes No No 4d 2.81 2.61 2.95 3.4 High Yes No Yes Yes No 4e 3.04 2.97 3.26 3.64 High Yes No Yes Yes Yes 4f -4.25 1.97 3.27 2.39 High No Yes Yes No No 4g 2.16 2.83 2.59 2.89 High Yes No Yes No No 4h 2.42 2.13 2.65 2.97 High Yes No No No No 4i -4.98 2.27 3.27 2.39 High No Yes Yes No No 4j 1.64 0.6 0.68 1.98 High No No Yes No No 4k 3.27 3.33 3.65 3.88 High Yes No Yes Yes Yes 4l -4.63 2.63 3.66 2.63 High No Yes Yes No No © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 509
  16. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Compound Rakesh Devidas Amrutkar et al. absorption CYP2C19 permeant XLOGP3 substrate WLOGP MLOGP inhibitor inhibitor inhibitor CYP1A2 CYP2C9 iLOGP Code BBB Pgp GI 4m 2.56 2.79 3.04 3.21 High Yes No Yes No Yes 4n -4.06 2.63 3.66 2.63 High No Yes Yes No No 4o 2.05 0.96 1.07 2.27 High Yes No Yes No No 4p 3.66 4.32 4.41 4.49 High Yes No Yes Yes Yes 4q -6.77 3.32 4.42 3.25 High No Yes Yes No No 4r 2.92 3.48 3.8 3.55 High Yes No Yes Yes Yes 4s -4.34 3.32 4.42 3.25 High No Yes Yes No No 4t 2.56 1.65 1.83 2.95 High Yes No Yes No No Table 11: Toxicity profiles of 20 ligands using Protox-II -prediction of toxicity of chemicals Hepatotoxicity LD 50 (mg/kg) Hydrocarbon accuracy (%) Compound Predicted Predicted Receptor Immuno genecity Toxicity Carcino genicity toxicity Muta Code Aryl 4a 859 100 -- -- -- -- -- 4b 859 69.26 Active Active -- Active Active 4c 751 69.26 Active Active -- Active Active 4d 1500 72.97 -- -- -- -- -- 4e 580 70.97 -- -- -- Active -- 4f 580 70.97 Active Active -- Active -- 4g 751 69.26 Active -- -- -- -- 4h 680 70.97 -- -- -- -- -- 4i 1400 70.97 Active Active -- Active Active 4j 751 69.26 Active Active -- Active -- 4k 680 70.97 -- -- -- Active -- 4l 680 69.26 -- Active -- Active -- 4m 680 70.97 -- -- -- -- -- 4n 1400 69.26 Active Active -- Active -- 4o 751 69.26 Active Active -- Active -- 4p 680 69.26 -- -- -- -- -- 4q 500 69.26 -- -- Active Active -- 4r 680 69.26 -- -- -- -- -- 4s 1400 69.26 -- -- Active Active -- 4t 751 67.38 Active Active -- Active -- 4. CONCLUSIONS disubstituted quinazolin-4(3H)-one binding mechanism was successfully replicated. According Molecular Docking. By using an automated to the docking simulation, the hydrophobic Van der docking tool called MDS version 4.6, the Waals, H-bond contacts, charge interactions, and Staphylococcus aureus crystal structure and 2,3- change in the series that improves binding potential © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 510
  17. 25728288, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/vjch.202200219 by Readcube (Labtiva Inc.), Wiley Online Library on [01/05/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Vietnam Journal of Chemistry Prediction of ADME/Tox properties, 2D,3D QSA… are in charge of creating stable compounds of Consent for Publication. No Patients /Volunteers/ ligands with receptors. According to table 2, the guardians of the children were involved for this ligands 4k, 4l, and 4m were shown to have the study. The methodology of the study was based on lowest dock scores or the lowest binding energy in software. kcal/mol, indicating that they had a higher affinity for the receptor's active site. It is evident that Availability of Data and Materials. Not molecules with a low dock score and binding energy Applicable. have a greater affinity for the receptor. Funding. No funding agency is involved in the 2D, 3D QSAR. A series of quinazoline-4-one (20 present study. molecules) derivatives underwent 2D and 3D QSAR analysis to determine their antimicrobial effects on Conflict of interest. None Declared. S. aureus. The molecular activity was transformed into log 1/C. The 2D-QSAR models with the highest Acknowledgement. The authors are grateful to the statistical significance are r2 = 0.8066 and q2 = Management and Principal of B.N. College of 0.6789. Results of 3D QSAR for internal and Pharmacy, Udaipur, K. K. Wagh College of external validation criteria (q2 = 0.7157 and Pharmacy, Nasik and VLife sciences Pvt. Ltd. Pune predicted r2 = 0.4634). The binding affinities are (www.vlifesciences.com) for providing necessary thus mostly determined by steric as well as facilities. electrostatic effects, according to 3D QSAR models. DeltaEpsilonB and DeltaPsiA descriptors were key REFERENCES contributing descriptors, according to 2D QSAR 1. W. Yu, A. D. MacKerell. Computer-aided drug design investigations. Some fresh compounds with better methods, Methods Mol. Biol., 2017, 1520, 85-106. activity than those previously reported were created using the best models that could be found. Chem. 2. G. Sliwoski, S. Kothiwale, J. Meiler, E. W. Lowe. Computational methods in drug discovery, Spider's confirmation that the structures had not Pharmacol.l Rev., 2014, 66(1), 334-395. previously been reported anywhere. The conclusions 3. Surabhi Surabhi, SK Singh. Computer Aided Drug reached to derived chemical entities useful for Design: An Overview, Journal of Drug Delivery and further designing novel anti-microbial agent. Therapeutics, 2018, 8(5), 504-509. 4. Discovery D. Target validation. Available from: ADMET Profiling. We have analyzed various http://www.microcal.com/drug-discovery- phamrmacokinetic and pharmacodynamics evelopment/biotherapeutics/targetvalidation.asp. properties of newly designed analogs, by means of 5. N. Prakash, P. Devangi. Drug Discovery, J. Antivir. swissADME online software and QikpropTool of Antiretrovir, 2010, 2, 063-068. Schrodinger_ 2015 (Maestro 10.2 version) as a 6. Pradeep, P. Heuristics for scaling up distributed result all compounds shows high GI absorption, protein docking. Marquette University, 2011. most of the compounds crosses BBB and Pgp, all compounds inhibits CYP1A2 except 4h. 7. O. A. Fathalla, E. M. Kassem, N. M. Ibrahem, M. M. Kamel. Synthesis of some new quinazolin-4-one Pharmacodynamics properties (toxicity profile) were derivatives and evaluation of their antimicrobial and also predicted by Protox-II tool. From these toxicity antiinflammatory effects, Acta Pol Pharm., 2008, studies it was found that ligand 4a, 4d, 4h, 4m, 4p 65(1), 11-20. and 4r do not show any type of toxicity. Compound 8. R. D. Amrutkar, S. V. Amrutkar, M. S. Ranawat. 4e and 4k show mutagenicity, Compound 4g shows Quinazolin-4-One: A Varsatile Molecule, Current hepatotoxicity. Bioactive Compounds, 2020, 16(4), 370-382. 9. J. P. Michael. Quinoline, quinazoline and acridone Ethics Approval and Consent to Participate. No alkaloids, Nat. Prod. Rep., 2007, 24, 223-246. human or animal subject was enrolled for the 10. S. B. Mhaske, N. P. Argade The chemistry of current study. The methodology of the study was recently isolated naturally occurring quinazolinone purely in-vitro. So, no ethical clearance required for alkaloids, Tetrahedron, 2006, 62, 9787-9826. this study. 11. M. C. Tseng, H. Y. Yang, Y. H. Chu Total synthesis of asperlicin C, circumdatin F, demethylbenzomalvin Human and Animal Rights. No human or animal A, demethoxycircumdatin H, sclerotigenin, and other subject was enrolled for the current study. The fused quinazolinones, Org. Biomol. Chem., 2010, 8, methodology of the study was purely in-vitro. 419-427. © 2023 Vietnam Academy of Science and Technology, Hanoi & Wiley-VCH GmbH www.vjc.wiley-vch.de 511
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